Title: Performance index assessment of intelligent computing methods in e-learning systems

Authors: Aditya Khamparia; Babita Pandey

Addresses: Department of Computer Science and Engineering, Lovely Professional University, Jalandhar, Punjab, India ' Department of Computer Applications, Lovely Professional University, Jalandhar, Punjab, India

Abstract: In the current advancing and smart growing technology e-learning system strikes the most dominant position for the learning style. Many research studies have evaluated e-learning system by using various criteria like prediction accuracy, satisfaction degree, pre-post analysis etc., but none of the results have explored the common methodology for appraising such systems. The proposed research work is focused on resolving the drawbacks of common benchmarks for evaluating the performance of e-learning system by including the importance (I), complexity (CC) and also determined the measurements of different learning problems and learning techniques. Finally, the performance index (PI) is computed on the basis of I and CC, which is represented on graphs with comparative view of importance (I), complexity (CC) and performance index (PI) for all the models.

Keywords: learning problem importance; LPI; learning problem measurement; LPM; learning technique complexity; LTCC; learning problems complexity; LPCC; PI.

DOI: 10.1504/IJAIP.2022.126689

International Journal of Advanced Intelligence Paradigms, 2022 Vol.23 No.3/4, pp.248 - 261

Received: 09 Jan 2017
Accepted: 04 Oct 2017

Published online: 03 Nov 2022 *

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